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Webinar - Analyzing Video

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Presented by Guy Rapoport (June 16, 2016)

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Webinar - Analyzing Video

  1. 1. Dato Confidential1 Analyzing Video with GraphLab Create June 16, 2016 Guy Rapaport, Data Scientist, Dato EMEA guy@dato.com
  2. 2. Dato Confidential2 Dato: We Intelligent Applications
  3. 3. Dato Confidential Some of our Customers 3
  4. 4. Dato Confidential4 Business must be intelligent Machine learning applications • Recommenders • Fraud detection • Ad targeting • Financial models • Personalized medicine • Churn prediction • Smart UX (video & text) • Personal assistants • IoT • Socials networks • Log analysis Last decade: Data management Now: Intelligent apps ? Last 5 years: Traditional analytics
  5. 5. Dato Confidential
  6. 6. Dato Confidential Creating a model pipeline exploration data modeling - Images - Text - Graphs - Tabular Data
  7. 7. Dato Confidential Creating a model pipeline Ingest Transform Model Deploy Unstructured Data
  8. 8. Dato Confidential Creating a model pipeline using Dato products Ingest Transform Model Deploy Unstructured Data SFrame Engine (FREE, open source) GraphLab Create (Scalable Machine Learning Python Library, 4K/machine/year) Predictive Services (Serving + Load Balancing + AB Testing, 10K/machine/year)
  9. 9. Dato Confidential9 $ pip install –U graphlab-create
  10. 10. Dato Confidential10 What will we cover today? 1. Match a movie’s screenplay with its subtitles. - Now we know who says what and when. 2. Extract frames, then actors’ faces, from the movie. - We’ll use opencv for video manipulation and face detection. 3. Train a face recognition model over the faces. - What’s the smallest portion of the movie we can get good results from? 10
  11. 11. Dato Confidential11 Python vs. Anaconda • You can download Python for free from python.org . - Python with its standard library. • Or, you could download the Anaconda distribution. - Python + tons of installed packages + package managers. • It’s the same Python, but Anaconda includes both pip and also with it’s own package manager, conda. 11
  12. 12. Dato Confidential12 pip vs. conda vs. virtualenv pip – install Python packages. conda – install Python packages + any OS packages required for your package to work (libraries etc). $ conda install -c menpo opencv3=3.1.0 virtualenv – separate environment (by manipulating the $PYTHONPATH etc.) so packages won’t break. You can have multiple Python versions on the same machine, and use a Python version in different environments. 12
  13. 13. Dato Confidential13 Look Deeper! 1) Building a Face Recognition System with OpenCV in the blink of an Eye • https://github.com/rragundez/PyData • Live video from webcam, online analytics 2) Using mxnet for deep feature extraction • https://github.com/dmlc/mxnet/blob/master/example/notebooks/predict- with-pretrained-model.ipynb • mxnet is now integrated into GraphLab! 3) mxnet-face • https://github.com/tornadomeet/mxnet-face
  14. 14. Dato Confidential Confidential – Dato internal use only. ©2015 Dato, Inc. Questions? “For the purpose of learning the Answer to the Ultimate Question of Life, The Universe, and Everything, the supercomputer Deep Thought was specially built. It takes Deep Thought 7½ million years to compute and check the answer, which turns out to be 42. Deep Thought points out that the answer seems meaningless because the beings who instructed it never actually knew what the Question was.” - Douglas Adams, “The Hitchhiker’s Guide to the Galaxy”
  15. 15. Dato Confidential15 Our Machine Learning Specialization in Coursera https://www.coursera.org/learn/ml-foundations
  16. 16. Dato Confidential Confidential – Dato internal use only. ©2015 Dato, Inc. Thanks! Install using pip: $ pip install -U graphlab-create Dato Launcher Download: https://dato.com/download/ The benchmarks on GitHub: https://github.com/guy4261/glc_pagerank_benchmark Coursera Course: https://www.coursera.org/learn/ml-foundations Reach out: guy@dato.com

Presented by Guy Rapoport (June 16, 2016)

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